961 resultados para Cognitive analysis


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For years, researchers and human resources specialists have been searching for predictors of performance as well as for relevant performance dimensions (Barrick & Mount, 1991; Borman & Motowidlo, 1993; Campbell, 1990; Viswesvaran et al., 1996). In 1993, Borman and Motowidlo provided a framework by which traditional predictors such as cognitive ability and the Big Five personality factors predicted two different facets of performance: 1) task performance and 2) contextual performance. A meta-analysis was conducted to assess the validity of this model as well as that of other modified models. The relationships between predictors such as cognitive ability and personality variables and the two outcome variables were assessed. It was determined that even though the two facets of performance may be conceptually different, empirically they overlapped substantially (p= .75). Finally, results show that there is some evidence for cognitive ability as a predictor of both task and contextual performance and conscientiousness as a predictor of both task and contextual performance. The possible mediation of predictor-- criterion relationships was also assessed. The relationship between cognitive ability and contextual performance vanished when task performance was controlled.

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The Unified Modeling Language (UML) has quickly become the industry standard for object-oriented software development. It is being widely used in organizations and institutions around the world. However, UML is often found to be too complex for novice systems analysts. Although prior research has identified difficulties novice analysts encounter in learning UML, no viable solution has been proposed to address these difficulties. Sequence-diagram modeling, in particular, has largely been overlooked. The sequence diagram models the behavioral aspects of an object-oriented software system in terms of interactions among its building blocks, i.e. objects and classes. It is one of the most commonly-used UML diagrams in practice. However, there has been little research on sequence-diagram modeling. The current literature scarcely provides effective guidelines for developing a sequence diagram. Such guidelines will be greatly beneficial to novice analysts who, unlike experienced systems analysts, do not possess relevant prior experience to easily learn how to develop a sequence diagram. There is the need for an effective sequence-diagram modeling technique for novices. This dissertation reports a research study that identified novice difficulties in modeling a sequence diagram and proposed a technique called CHOP (CHunking, Ordering, Patterning), which was designed to reduce the cognitive load by addressing the cognitive complexity of sequence-diagram modeling. The CHOP technique was evaluated in a controlled experiment against a technique recommended in a well-known textbook, which was found to be representative of approaches provided in many textbooks as well as practitioner literatures. The results indicated that novice analysts were able to perform better using the CHOP technique. This outcome seems have been enabled by pattern-based heuristics provided by the technique. Meanwhile, novice analysts rated the CHOP technique more useful although not significantly easier to use than the control technique. The study established that the CHOP technique is an effective sequence-diagram modeling technique for novice analysts.

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Acknowledgements This article is based on a doctoral research project of the first author which was sponsored by an international drilling rig operator. The views presented are those of the authors and should not be taken to represent the position or policy of the sponsor. The authors wish to thank the industrial supervisor and the drilling experts for their contribution and patience, as well as Aberdeen Drilling School for allowing the first author to attend one of their well control courses.

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Vascular cognitive impairment (VCI), including its severe form, vascular dementia (VaD), is the second most common form of dementia. The genetic etiology of sporadic VCI remains largely unknown. We previously conducted a systematic review and meta-analysis of all published genetic association studies of sporadic VCI prior to 6 July 2012, which demonstrated that APOE (ɛ4, ɛ2) and MTHFR (rs1801133) variants were associated with susceptibility for VCI. De novo genotyping was conducted in a new independent relatively large collaborative European cohort of VaD (nmax = 549) and elderly non-demented samples (nmax = 552). Where available, genotype data derived from Illumina's 610-quad array for 1210 GERAD1 control samples were also included in analyses of genes examined. Associations were tested using the Cochran-Armitage trend test: MTHFR rs1801133 (OR = 1.36, 95% CI 1.16-1.58, p = <0.0001), APOE rs7412 (OR = 0.62, 95% CI 0.42-0.90, p = 0.01), and APOE rs429358 (OR = 1.59, 95% CI 1.17-2.16, p = 0.003). Association was also observed with APOE epsilon alleles; ɛ4 (OR = 1.85, 95% CI 1.35-2.52, p = <0.0001) and ɛ2 (OR = 0.67, 95% CI 0.46-0.98, p = 0.03). Logistic Regression and Bonferroni correction in a subgroup of the cohort adjusted for gender, age, and population maintained the association of APOE rs429358 and ɛ4 allele.

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Verbal fluency is the ability to produce a satisfying sequence of spoken words during a given time interval. The core of verbal fluency lies in the capacity to manage the executive aspects of language. The standard scores of the semantic verbal fluency test are broadly used in the neuropsychological assessment of the elderly, and different analytical methods are likely to extract even more information from the data generated in this test. Graph theory, a mathematical approach to analyze relations between items, represents a promising tool to understand a variety of neuropsychological states. This study reports a graph analysis of data generated by the semantic verbal fluency test by cognitively healthy elderly (NC), patients with Mild Cognitive Impairment – subtypes amnestic(aMCI) and amnestic multiple domain (a+mdMCI) - and patients with Alzheimer’s disease (AD). Sequences of words were represented as a speech graph in which every word corresponded to a node and temporal links between words were represented by directed edges. To characterize the structure of the data we calculated 13 speech graph attributes (SGAs). The individuals were compared when divided in three (NC – MCI – AD) and four (NC – aMCI – a+mdMCI – AD) groups. When the three groups were compared, significant differences were found in the standard measure of correct words produced, and three SGA: diameter, average shortest path, and network density. SGA sorted the elderly groups with good specificity and sensitivity. When the four groups were compared, the groups differed significantly in network density, except between the two MCI subtypes and NC and aMCI. The diameter of the network and the average shortest path were significantly different between the NC and AD, and between aMCI and AD. SGA sorted the elderly in their groups with good specificity and sensitivity, performing better than the standard score of the task. These findings provide support for a new methodological frame to assess the strength of semantic memory through the verbal fluency task, with potential to amplify the predictive power of this test. Graph analysis is likely to become clinically relevant in neurology and psychiatry, and may be particularly useful for the differential diagnosis of the elderly.

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Verbal fluency is the ability to produce a satisfying sequence of spoken words during a given time interval. The core of verbal fluency lies in the capacity to manage the executive aspects of language. The standard scores of the semantic verbal fluency test are broadly used in the neuropsychological assessment of the elderly, and different analytical methods are likely to extract even more information from the data generated in this test. Graph theory, a mathematical approach to analyze relations between items, represents a promising tool to understand a variety of neuropsychological states. This study reports a graph analysis of data generated by the semantic verbal fluency test by cognitively healthy elderly (NC), patients with Mild Cognitive Impairment – subtypes amnestic(aMCI) and amnestic multiple domain (a+mdMCI) - and patients with Alzheimer’s disease (AD). Sequences of words were represented as a speech graph in which every word corresponded to a node and temporal links between words were represented by directed edges. To characterize the structure of the data we calculated 13 speech graph attributes (SGAs). The individuals were compared when divided in three (NC – MCI – AD) and four (NC – aMCI – a+mdMCI – AD) groups. When the three groups were compared, significant differences were found in the standard measure of correct words produced, and three SGA: diameter, average shortest path, and network density. SGA sorted the elderly groups with good specificity and sensitivity. When the four groups were compared, the groups differed significantly in network density, except between the two MCI subtypes and NC and aMCI. The diameter of the network and the average shortest path were significantly different between the NC and AD, and between aMCI and AD. SGA sorted the elderly in their groups with good specificity and sensitivity, performing better than the standard score of the task. These findings provide support for a new methodological frame to assess the strength of semantic memory through the verbal fluency task, with potential to amplify the predictive power of this test. Graph analysis is likely to become clinically relevant in neurology and psychiatry, and may be particularly useful for the differential diagnosis of the elderly.

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Alzheimer's disease (AD) is becoming a growing global problem, and there is an urgent need to identify reliable blood biomarkers of the risk and progression of this condition. A potential candidate is the brain-derived neurotrophic factor (BDNF), which modulates major trophic effects in the brain. However, findings are apparently inconsistent regarding peripheral blood BDNF levels in AD patients vs. healthy people. We thus performed a systematic review and meta-analysis of the studies that have examined peripheral BDNF levels in patients with AD or mild cognitive impairment (MCI) and healthy controls. We searched articles through PubMed, EMBASE, and hand searching. Over a total pool of 2061 potential articles, 26 met all inclusion criteria (including a total of 1584 AD patients, 556 MCI patients, and 1294 controls). A meta-analysis of BDNF levels between early AD and controls showed statistically significantly higher levels (SMD [95 % CI]: 0.72 [0.31, 1.13]) with no heterogeneity. AD patients with a low (<20) mini-mental state examination (MMSE) score had lower peripheral BDNF levels compared with controls (SMD [95 % CI]: -0.33 [-0.60, -0.05]). However, we found no statistically significant difference in blood (serum/plasma) BDNF levels between all AD patients and controls (standard mean difference, SMD [95 % CI]: -0.16 [-0.4, 0.07]), and there was heterogeneity among studies (P < 0.0001, I 2 = 85.8 %). There were no differences in blood BDNF levels among AD or MCI patients vs. controls by subgroup analyses according to age, sex, and drug use. In conclusion, this meta-analysis shows that peripheral blood BDNF levels seem to be increased in early AD and decreased in AD patients with low MMSE scores respectively compared with their age- and sex-matched healthy referents. At present, however, this could not be concluded from individual studies.

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Neuroimaging research involves analyses of huge amounts of biological data that might or might not be related with cognition. This relationship is usually approached using univariate methods, and, therefore, correction methods are mandatory for reducing false positives. Nevertheless, the probability of false negatives is also increased. Multivariate frameworks have been proposed for helping to alleviate this balance. Here we apply multivariate distance matrix regression for the simultaneous analysis of biological and cognitive data, namely, structural connections among 82 brain regions and several latent factors estimating cognitive performance. We tested whether cognitive differences predict distances among individuals regarding their connectivity pattern. Beginning with 3,321 connections among regions, the 36 edges better predicted by the individuals' cognitive scores were selected. Cognitive scores were related to connectivity distances in both the full (3,321) and reduced (36) connectivity patterns. The selected edges connect regions distributed across the entire brain and the network defined by these edges supports high-order cognitive processes such as (a) (fluid) executive control, (b) (crystallized) recognition, learning, and language processing, and (c) visuospatial processing. This multivariate study suggests that one widespread, but limited number, of regions in the human brain, supports high-level cognitive ability differences. Hum Brain Mapp, 2016. © 2016 Wiley Periodicals, Inc.

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The spectrum of radiofrequency is distributed in such a way that it is fixed to certain users called licensed users and it cannot be used by unlicensed users even though the spectrum is not in use. This inefficient use of spectrum leads to spectral holes. To overcome the problem of spectral holes and increase the efficiency of the spectrum, Cognitive Radio (CR) was used and all simulation work was done on MATLAB. Here analyzed the performance of different spectrum sensing techniques as Match filter based spectrum sensing and energy detection, which depend on various factors, systems such as Numbers of input, signal-to-noise ratio ( SNR Ratio), QPSK system and BPSK system, and different fading channels, to identify the best possible channels and systems for spectrum sensing and improving the probability of detection. The study resulted that an averaging filter being better than an IIR filter. As the number of inputs and SNR increased, the probability of detection also improved. The Rayleigh fading channel has a better performance compared to the Rician and Nakagami fading channel.

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This study aimed to evaluate long-term atrophy in contralateral hippocampal volume after surgery for unilateral MTLE, as well as the cognitive outcome for patients submitted to either selective transsylvian amygdalohippocampectomy (SelAH) or anterior temporal lobe resection (ATL). We performed a longitudinal study of 47 patients with MRI signs of unilateral hippocampal sclerosis (23 patients with right-sided hippocampal sclerosis) who underwent surgical treatment for MTLE. They underwent preoperative/postoperative high-resolution MRI as well as neuropsychological assessment for memory and estimated IQ. To investigate possible changes in the contralateral hippocampus of patients, we included 28 controls who underwent two MRIs at long-term intervals. The volumetry using preoperative MRI showed significant hippocampal atrophy ipsilateral to the side of surgery when compared with controls (p<0.0001) but no differences in contralateral hippocampal volumes. The mean postoperative follow-up was 8.7 years (± 2.5 SD; median=8.0). Our patients were classified as Engel I (80%), Engel II (18.2%), and Engel III (1.8%). We observed a small but significant reduction in the contralateral hippocampus of patients but no volume changes in controls. Most of the patients presented small declines in both estimated IQ and memory, which were more pronounced in patients with left TLE and in those with persistent seizures. Different surgical approaches did not impose differences in seizure control or in cognitive outcome. We observed small declines in cognitive scores with most of these patients, which were worse in patients with left-sided resection and in those who continued to suffer from postoperative seizures. We also demonstrated that manual volumetry can reveal a reduction in volume in the contralateral hippocampus, although this change was mild and could not be detected by visual analysis. These new findings suggest that dynamic processes continue to act after the removal of the hippocampus, and further studies with larger groups may help in understanding the underlying mechanisms.

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this study aimed to investigate the cognitive and behavioral profiles, as well as the psychiatric symptoms and disorders in children with three different genetic syndromes with similar sociocultural and socioeconomic backgrounds. thirty-four children aged 6 to 16 years, with Williams-Beuren syndrome (n=10), Prader-Willi syndrome (n=11), and Fragile X syndrome (n=13) from the outpatient clinics of Child Psychiatry and Medical Genetics Department were cognitively assessed through the Wechsler Intelligence Scale for Children (WISC-III). Afterwards, a full-scale intelligence quotient (IQ), verbal IQ, performance IQ, standard subtest scores, as well as frequency of psychiatric symptoms and disorders were compared among the three syndromes. significant differences were found among the syndromes concerning verbal IQ and verbal and performance subtests. Post-hoc analysis demonstrated that vocabulary and comprehension subtest scores were significantly higher in Williams-Beuren syndrome in comparison with Prader-Willi and Fragile X syndromes, and block design and object assembly scores were significantly higher in Prader-Willi syndrome compared with Williams-Beuren and Fragile X syndromes. Additionally, there were significant differences between the syndromes concerning behavioral features and psychiatric symptoms. The Prader-Willi syndrome group presented a higher frequency of hyperphagia and self-injurious behaviors. The Fragile X syndrome group showed a higher frequency of social interaction deficits; such difference nearly reached statistical significance. the three genetic syndromes exhibited distinctive cognitive, behavioral, and psychiatric patterns.

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The new social panorama resulting from aging of the Brazilian population is leading to significant transformations within healthcare. Through the cluster analysis strategy, it was sought to describe the specific care demands of the elderly population, using frailty components. Cross-sectional study based on reviewing medical records, conducted in the geriatric outpatient clinic, Hospital de Clínicas, Universidade Estadual de Campinas (Unicamp). Ninety-eight elderly users of this clinic were evaluated using cluster analysis and instruments for assessing their overall geriatric status and frailty characteristics. The variables that most strongly influenced the formation of clusters were age, functional capacities, cognitive capacity, presence of comorbidities and number of medications used. Three main groups of elderly people could be identified: one with good cognitive and functional performance but with high prevalence of comorbidities (mean age 77.9 years, cognitive impairment in 28.6% and mean of 7.4 comorbidities); a second with more advanced age, greater cognitive impairment and greater dependence (mean age 88.5 years old, cognitive impairment in 84.6% and mean of 7.1 comorbidities); and a third younger group with poor cognitive performance and greater number of comorbidities but functionally independent (mean age 78.5 years old, cognitive impairment in 89.6% and mean of 7.4 comorbidities). These data characterize the profile of this population and can be used as the basis for developing efficient strategies aimed at diminishing functional dependence, poor self-rated health and impaired quality of life.

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Background: High level piano performance requires complex integration of perceptual, motor, cognitive and emotive skills. Observations in psychology and neuroscience studies have suggested reciprocal inhibitory modulation of the cognition by emotion and emotion by cognition. However, it is still unclear how cognitive states may influence the pianistic performance. The aim of the present study is to verify the influence of cognitive and affective attention in the piano performances. Methods and Findings: Nine pianists were instructed to play the same piece of music, firstly focusing only on cognitive aspects of musical structure (cognitive performances), and secondly, paying attention solely on affective aspects (affective performances). Audio files from pianistic performances were examined using a computational model that retrieves nine specific musical features (descriptors) - loudness, articulation, brightness, harmonic complexity, event detection, key clarity, mode detection, pulse clarity and repetition. In addition, the number of volunteers' errors in the recording sessions was counted. Comments from pianists about their thoughts during performances were also evaluated. The analyses of audio files throughout musical descriptors indicated that the affective performances have more: agogics, legatos, pianos phrasing, and less perception of event density when compared to the cognitive ones. Error analysis demonstrated that volunteers misplayed more left hand notes in the cognitive performances than in the affective ones. Volunteers also played more wrong notes in affective than in cognitive performances. These results correspond to the volunteers' comments that in the affective performances, the cognitive aspects of piano execution are inhibited, whereas in the cognitive performances, the expressiveness is inhibited. Conclusions: Therefore, the present results indicate that attention to the emotional aspects of performance enhances expressiveness, but constrains cognitive and motor skills in the piano execution. In contrast, attention to the cognitive aspects may constrain the expressivity and automatism of piano performances.

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This paper presents an analysis of dysfluencies in two oral tellings of a familiar children's story by a young boy with autism. Thurber & Tager-Flusberg (1993) postulate a lower degree of cognitive and communicative investment to explain a lower frequency of non-grammatical pauses observed in elicited narratives of children with autism in comparison to typically developing and intellectually disabled controls. we also found a very low frequency of non-grammatical pauses in our data, but indications of high engagement and cognitive and communicative investment. We point to a wider range of disfluencies as indicators of cognitive load, and show that the kind and location of dysfluencies produced may reveal which aspects of the narrative task are creating the greatest cognitive demand: here, mental state ascription, perspectivization, and adherence to story schema. This paper thus generates analytical options and hypotheses that can be explored further in a larger population of children with autism and typically developing controls.

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